




'''simple docstring'''



import operator as op


UpperCamelCase_    	=				"scaler.pt"
UpperCamelCase_    	=				"pytorch_model"
UpperCamelCase_    	=				"random_states"
UpperCamelCase_    	=				"optimizer"
UpperCamelCase_    	=				"scheduler"
UpperCamelCase_    	=				"pytorch_model.bin"
UpperCamelCase_    	=				"pytorch_model.bin.index.json"
UpperCamelCase_    	=				"model.safetensors"
UpperCamelCase_    	=				"model.safetensors.index.json"
UpperCamelCase_    	=				"1.10.2"
UpperCamelCase_    	=				"py38"
UpperCamelCase_    	=				"4.17.0"
UpperCamelCase_    	=				["ml.p3.16xlarge", "ml.p3dn.24xlarge", "ml.p4dn.24xlarge"]
UpperCamelCase_    	=				["FULL_SHARD", "SHARD_GRAD_OP", "NO_SHARD", "HYBRID_SHARD", "HYBRID_SHARD_ZERO2"]
UpperCamelCase_    	=				["TRANSFORMER_BASED_WRAP", "SIZE_BASED_WRAP", "NO_WRAP"]
UpperCamelCase_    	=				["BACKWARD_PRE", "BACKWARD_POST", "NO_PREFETCH"]
UpperCamelCase_    	=				["FULL_STATE_DICT", "LOCAL_STATE_DICT", "SHARDED_STATE_DICT"]
UpperCamelCase_    	=				"2.0.1"
UpperCamelCase_    	=				["pdsh", "standard", "openmpi", "mvapich"]
UpperCamelCase_    	=				["default", "reduce-overhead", "max-autotune"]

UpperCamelCase_    	=				{">": op.gt, ">=": op.ge, "==": op.eq, "!=": op.ne, "<=": op.le, "<": op.lt}

# These are the args for `torch.distributed.launch` for pytorch < 1.9
UpperCamelCase_    	=				[
    "nnodes",
    "nproc_per_node",
    "rdzv_backend",
    "rdzv_endpoint",
    "rdzv_id",
    "rdzv_conf",
    "standalone",
    "max_restarts",
    "monitor_interval",
    "start_method",
    "role",
    "module",
    "m",
    "no_python",
    "run_path",
    "log_dir",
    "r",
    "redirects",
    "t",
    "tee",
    "node_rank",
    "master_addr",
    "master_port",
]

UpperCamelCase_    	=				["DEEPSPEED", "MULTI_GPU", "FSDP", "MEGATRON_LM"]
UpperCamelCase_    	=				["DEEPSPEED", "MULTI_XPU", "FSDP"]



def 							UpperCAmelCase		(       lowercase				):







				"""simple docstring"""



				if not isinstance(lowercase				,     lowercase				):
								raise ValueError('''Input must be an integer'''				)
				if input_num <= 0:
								raise ValueError('''Input must be positive'''				)
				return sum(
				    divisor for divisor in range(1				,     input_num // 2 + 1				) if input_num % divisor == 0				)


if __name__ == "__main__":
		import doctest

		doctest.testmod()